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Artificial intelligence for crew scheduling in aviation sector

This research aims to relive the factors on applying AI in crew scheduling and rostering on low-cost airlines, IndiGO Airlines was chosen as base, to minimize the time and effort of human resources and increase effectiveness. This research looks into the possibility of utilizing artificial intelligence proposed model to schedule through a decision support system to reduce mistake from human intervention. Techniques employed includes of extensive literature searches, six qualitative interviews with two respondents per industry and 109 quantitative online surveys for crew scheduling department respondents. The data collected from the survey was analyzed and presented in the form of graphs to ease interpretation of the this research by concentrating on the challenges and costs involved in Artificial Intelligence. Thus, the techniques such as Data reduction and abduction logic have been used to find the sound information out of the whole set of information.From the survey results and interview questions, there are major benefits of incorporating AI in crew scheduling and rostering. The study also presents the best approach that low-cost airlines can adopt to lower errors and uphold performance, effectively showing that the adoption of AI in the industry is significantly beneficial

Author: Slavia Robert Kanjirethingal

Supervisor: Nadežda Spiridovska

Degree: Professional Master

Year: 2024

Work Language: English

Study programme: Aviation Management

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Optimizing Product Cost in Supply Chain

Optimizing product cost through simulation modeling offers a powerful approach to enhancing cost efficiency and decision-making in product development and manufacturing. Simulation modeling allows businesses to create detailed virtual representations of their processes, enabling them to experiment with different scenarios and strategies without the risks associated with physical trials. Simulation modeling supports iterative testing and optimization, allowing for the refinement of product designs and manufacturing processes. Ultimately, this approach enhances the ability to make informed, data-driven decisions, leading to more effective cost management and improved profitability. This abstract highlights the value of simulation modeling in optimizing product cost, emphasizing its role in providing actionable insights and fostering strategic improvements.

Author: Sofiya Andryuk

Supervisor: Mihails Savrasovs

Degree: Professional Bachelor

Year: 2024

Work Language: English

Development of Cross Platform 2D Games using OpenGL and ImGui Libraries

The aim of this bachelor's work was to develop a cross platform application containing two 2D games - Tetris and Snake. In the course of the work the subject area was analyzed and present analogues compared. The requirements were formulated based on the analysis conclusions. Soon after the model of requirements was created where the actors were identified and use cases developed. Based on the developed use cases a Use Case diagram was built as well as sequence diagrams and preliminary class diagram. During implementation stage, the software was developed in C++ language using OpenGL and Dear ImGui graphical libraries. In the end 2 games were developed. Finally, the developed software was tested. Test results showed that developed application in the process of completing the bachelor's work fully complies with all the requirements for it.

Author: Staņislavs Ņilovs

Supervisor: Karina Kostjkina

Degree: Bachelor

Year: 2024

Work Language: English

Study programme: Computer Science

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Key factors of financial resilience in the market segment of full service carriers in crises

This thesis focuses on a detailed analysis of the financial resilience factors within the airlines of the full-service market segment. The thesis is based on exploring the factors that enable airlines to manage and recover from disruptions effectively. By examining the airline industry's response to the disruptions, the thesis shows important elements such as financial stability, operational agility, strategic foresight, and important management methodologies to survive crises. Additionally, important factors and important strategies and scenarios will be shown to survive and to be resilient within crises. Furthermore, the role of governmental aids and their methods, in the form of financial aid and flexibility, is examined and also shows the importance in lowering negative economic effects for the industry in crisis. The thesis also shows how important effective collaboration between airlines, regulatory authorities, and other stakeholders can help to manage crises effectively. Taking all this into account, the thesis is to show how financial resilience in the airline industry can be described in different ways. Moreover, it reveals the importance of strategic planning in network, operation and finance to handle further crises in future.

Author: Stefan Bonhardt

Supervisor: Jeļena Popova

Degree: Professional Master

Year: 2024

Work Language: English

Study programme: Aviation Management

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CNN-Based pipeline-related artifact and damage recognition in IHC staining as preprocessing step for pathological analysis

This work proposes automated solution for artifact and damage segmentation in biomedical images using machine learning algorithms. The development process includes data preprocessing, label classification using a clustering algorithm and segmentation model. CNN architectures like YOLO and U-NET are utilized for segmentation, and K-Means and DBSC algorithms are evaluated for clustering. The outcomes include a set of data preprocessing precodures, clustering algorithm testing and results analysis, segmentation model and recommendations for further development.

Author: Taisija Kožarina

Supervisor: Jeļena Kijonoka

Degree: Bachelor

Year: 2024

Work Language: English

Study programme: Computer Science

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